Fetch forest data from Statistics Finland

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Data was downloaded (by hand, API was not found) from VMI laskentapalvelu (Valtakunnallinen mets??inventaari), and the data was from years 2009-2013. Parameters for the data download: forest area, tree volume, and tree number were searchded for 20-year age groups, areas categorised by the main tree species, seach including both forests and kitumaa (poorly growing areas), and using district levels.

library(tidyverse)

## -- Attaching packages ------------------------------------------------------------------- tidyverse 1.2.1 --

## v ggplot2 3.1.1       v purrr   0.3.2  
## v tibble  2.1.1       v dplyr   0.8.0.1
## v tidyr   0.8.3       v stringr 1.4.0  
## v readr   1.3.1       v forcats 0.4.0

## -- Conflicts ---------------------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

library(OpasnetUtils)

## 
## Attaching package: 'OpasnetUtils'

## The following object is masked from 'package:dplyr':
## 
##     combine

# library(devtools)
# install_github("rOpenGov/statfi") # If not installed yet

#library(statfi) statfi is outdated. Use package pxweb instead.

parms <- data.frame(
  File = c(
    "ID1557142456655.csv",
    "ID1557142551382.csv",
    "ID1557142710762.csv"
  ),
  Variable = c("Pintaala","Runkoluku","Tilavuus"),
  Unit= c("km2","1000kpl","1000m3")
)
dat <- data.frame()
for(i in 1:nrow(parms)) {
  tmp <- read.csv(paste0("C:/Users/jtue/AppData/Local/Temp/Data-",parms$File[i]),
                header=TRUE, sep=";", skip=3,encoding = "UTF-8")
  colnames(tmp) <- c("Maakunta","Ikaluokka","Paapuulaji","Tulos","Keskivirhe","Suht_keskivirhe")
  for(j in 4:6) {tmp[[j]][is.na(tmp[[j]])] <- 0}
  dat <- rbind(dat, cbind(tmp, parms[i, 2:3]))
}  

## Warning in data.frame(..., check.names = FALSE): row names were found from
## a short variable and have been discarded

## Warning in data.frame(..., check.names = FALSE): row names were found from
## a short variable and have been discarded

## Warning in data.frame(..., check.names = FALSE): row names were found from
## a short variable and have been discarded

dat$Ikaluokka <- factor(dat$Ikaluokka, levels=c("Puuton","1-20","21-40","41-60","61-80","81-100",
                                                "101-120","121-140","141-160","161+"))
dat$Maakunta <- factor(dat$Maakunta, levels=unique(dat$Maakunta))
dat$Alue <- ifelse(as.numeric(dat$Maakunta) %in% 15:18, "Pohjois-Suomi", "Etel??-Suomi")

ggplot(dat[dat$Variable=="Tilavuus" , ], aes(x=Ikaluokka, weight=Tulos, fill=Maakunta))+geom_bar()+
  facet_grid(.~Alue)

tmp <- dat[dat$Variable=="Tilavuus",]
tmp <- aggregate(tmp["Tulos"], tmp[c("Alue","Ikaluokka")], sum)
pl <- tmp %>%
#  group_by(Alue) %>%
  plot_ly(x=~Ikaluokka, y=~Tulos/1000, color=~Alue, type="bar") %>%
  layout(
#    barmode="group",
    yaxis=list(title="Puuston tilavuus (M m3)")
  )
pl

## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels

## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels

# pushIndicatorGraph(pl, 124) # Does not work due to an unknown error

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